. Click Statistics 5.7 SpCICJ Use the States data set to analyze the rate of car
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Question
. Click Statistics 5.7 SpCICJ Use the States data set to analyze the rate of car theft (Carthft10). The independent variables population density (PopDense) and unem- Continue to r screen Click OK will be ployment rate (Unemplymnt). a. State the unst Click Analyze Regression Linear. equation. Move Carthft10 to the Dependent window and PopDense and Unemplymnt to the Independent b. State the stane tion. What is Which indep effect on Infa window. .Click Statistics and check Descriptives. Click Continue to return to the Linear Regression screen . Click OK a. State the unstandardized multiple regression equation. (HINT: The values for a and b are in the "Coefficients" box of the output, under the column labeled B. The value in the first row is a, c. Report the va variance in and the value in the second row is b.) independent this compar explained b (HINTS: R and you can "Correlatio b. State the standardized multiple regression equa- tion. What is the direction of each relationship? Which independent variable had the stronger effect on Carthft10? (HINT: The beta-weights are in the "Coefficients" box, under "Standardized Coefficients" and “Beta") Bivariate Infant Co. Sth c. Report the value of R2. What percentage of the variance in Carthft10 is explained by the two independent variables combined? How does this compare to the amount of the variance explained by each independent variable alone? (HINTS: R is in the "Model Summary" box, and you can compute values from the r's in the "Correlations" window of the output.) Multiple 15.9 SOC In probl base to analy cell phone usa capita), and ur and urbanizati at their combi Click Ana .Move Cel GNIcap ar Click Sta Continue Bivariate Carthft 10 and PopDense Multiple 15.8 SOC In problem 13.8, you used the States data- screenExplanation / Answer
Answer to the question is as below:
a.
Y = 61.702 -.049*X1 + 22.095*X2
Y = 50.573 - 0.151*Z1 + 7.518*Z2
b. Unemployment variables are in the positive direcion , People per square in the opposite of Rights
Unemployment has a stronger relationship on RIGHT , because it is more significant
c. 0.156 is the value of R square. 15.6% of the variance in RIGHTs is explained by the 2 independent variables combined
r can be got from the Pearson' correlation table, square it and you will get individual r squares. Hence,
GNIcap r = .038, r2 = .038^2 = .0014
IncomeIneq, r = .434, r2 = .1883
Multiple R2 = .156
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